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Hi Alex,

OK, sounds like you have done the sensible things.
Could you put your images and weighting volumes somewhere
for us to download (web page or ftp)?
We'll take a look at them at this end and see if there
is anything that can be done.

All the best,
        Mark



On Fri, 15 Oct 2004, Fornito, Alexander wrote:

> Hi,
> Thanks for your help - it's clarified a few things. However, I'm still
> having a bit of trouble. Maybe you can tell me where I'm going wrong.
> I've done what you suggested, trying to create a weight in the input
> space.
> I drew a mask around there areas of signal loss (orbital frontal and
> inferior temporal areas) and saved this out as a binary image file (in
> analyze format), with the mask valued at 0 and the rest (including
> non-brain) as 1. I then included this image as the input weight using
> the flirt GUI when registering the epi to the subjects T1, but it
> appears to have made little difference to the actual registration.
> I then tried again, this time drawing a mask around the ventricles and
> weighting them as 2, the signal dropout as 0, and the rest as 1, but
> again, there appears to be little difference in the registration
> results.
> Am I missing something?
> Thanks again,
> Alex
>
> -----Original Message-----
> From: Mark Jenkinson [mailto:[log in to unmask]]
> Sent: Friday, October 01, 2004 10:27 PM
> To: [log in to unmask]
> Subject: Re: [FSL] Registration woes
>
> Hi Alex,
>
> I agree with Tim.  Especially in that it is very important to
> distinguish
> masking from weighting - they are quite different operations.
>
> I would say that there isn't much advantage in smoothing the cost
> weights
> though, so you could easily ignore that step.
>
> Also, I never recommend drawing weights based on a non-weighted
> registration
> (using mricro's linked view or anything else) as it is only likely to be
> much good
> if the registration is good, which is not going to be true when you
> really need
> the weights the most.  Either draw it directly on the functions where
> you can
> see the signal loss (and use the -inweight) or draw a general one in the
> appropriate
> areas on a structural or standard-space image (and use the -refweight
> option).
> The latter saves a lot of time if you are doing this many times on
> different
> scans.
>
> It is also worth noting that the larger the ignored area in the weights
> (voxels
> with zero or near-zero values) then the less robust the initial search
> phase of
> the registration becomes.  So for weights with relative large areas
> being set
> near zero it is best to use "no search" either via the GUI pull-down
> options
> or by using -nosearch in the command line.  This will then require that
> the
> initial positions of the images are no more than say 20-30 degrees out
> of
> alignment, but as long as the slicing (sagittal, axial, oblique, etc) is
> the same
> or can be made the same (or nearly the same) using avwswapdim then
> there should be no problems.
>
> Hope this is also useful.
>
> All the best,
>     Mark
>
>
>
> Tim Behrens wrote:
>
> >Hi Alex,
> >
> >I'll have a go at answering these - Mark can correct me when I get it
> >wrong..
> >
> >
> >
> >>1 - Would I have to mask just the initial highres, or both the initial
> >>highres and task epi? If the latter, would I just mask the middle
> volume,
> >>as this is what is used in the registration? If so, my 4D file
> contains
> >>160 volumes. Would the middle correspond to the 79th, or the 80th?
> >>
> >>
> >
> >the cost function mask is a separate 3D image in reference (-refweight)
> or
> >input (-inweight) space ( you can actually apply both weightings if you
> >like, but they have to be in the right spaces). Note that Cost function
> >weighting is different from masking the original images, as masking
> >introduces artificial edges which will drive the registration - usually
> >not a good idea.
> >
> >
> >
> >
> >>2 - The CBU page recommends co-registering the epi to the structural
> and
> >>using the "yoke" function in MRIcro to identify points where there is
> >>signal dropout in the epi relative to the structural. These are the
> >>portions that should be masked out. If I register the unmasked epi to
> the
> >>structural, wouldn't this yield a (relatively) poor correspondance
> between
> >>the images, so that using this as the basis for identifying signal
> dropout
> >>would not be the best way to go about it? Are there any alternative
> ways
> >>for idetifying which areas to mask out?
> >>
> >>
> >>
> >
> >If you use -inweight, your cost function weight mask will be directly
> in
> >input space so you can just downweight the areas with susceptibility
> >artefact, and upweight the boundaries you trust ( lateral walls of the
> >ventricles etc.. ). If you wanted to you could apply a _generic_ MNI
> space
> >mask to the reference space (-refweight) which would do the same thing
> -
> >downweight occipital pole etc and upweight the ventricle walls. I guess
> >this would be slightly less accurate than doing it individually for
> each
> >input volume, but I would think you could downweight pretty big areas
> >without really detracting from the registration, so I would think this
> >should be fine.
> >
> >
> >
> >
> >>3 - Following from 2, would there be any problems in doing a straight
> >>image subtraction to identify the areas to be masked? It seems to me
> that
> >>this would be plagued by the same problems as in 2, but that it would
> be a
> >>quicker way to go about it?
> >>
> >>
> >
> >I think this is answered by the previous point (??)
> >
> >
> >
> >>4 - The CBU page recommends smoothing the mask image (8mm in
> accordance
> >>with the SPM default). Would I also need to do this with FEAT? Would I
> use
> >>5mm, as this is the FEAT default (or alternatively, whatever level I
> set
> >>it to)?
> >>
> >>
> >>
> >
> >I would think smoothing the mask image would be a good idea. However,
> the
> >smoothness here is different from the smoothness in Feat - here we are
> >smoothing because of uncertainty in the location of the structures of
> >interest, not due to GRF theory etc. In this case, I would thing 8mm
> >smoothing of the mask image would be fine.
> >
> >
> >
> >>5 - As an aside, can someone tell me why the average epi template in
> SPM
> >>would be a poor choice as an intial highres? Does the fact that it's
> not
> >>the same brain as your subject introduce more problems than the
> advantage
> >>of having the added contrast?
> >>
> >>
> >>
> >
> >Usually going to an initial highres, you would want to be able to
> choose a
> >low number of degrees of freedom to get a really robust registration.
> If
> >you use a reference brain which is a different global shape to the
> input
> >brain, you will need a high number of degrees of freedom even to get
> close
> >to a good registration, so I would think it would not be particularly
> >advantageous to choose an averaged brain as an initial highres.
> >
> >Hope this is useful (and accurate!!)
> >
> >
> >T
> >
> >
> >
> >
> >
> >
> >
> >>Sorry if some of these questions seem a bit basic - still trying to
> get my
> >>head around all of this!
> >>Thanks heaps, I really appreciate your ongoing help!
> >>Alex
> >>
> >>
> >>
>